Whole blood RNAseq from a large ALS case-control study at Univ of Michigan

Patients with amyotrophic lateral sclerosis (ALS), a rare fatal neurodegenerative disease, face a lengthy diagnostic process, and, although most survive only 2 to 4 years from diagnosis, lack information regarding their specific anticipated disease course due to a lack of prognostic tools. Although ALS is a heterogeneous disease of varied etiology, peripheral immune system dysfunction is ubiquitous, reflected in altered whole blood transcriptome. Herein, we profiled whole blood gene expression by RNA sequencing in a large cohort of ALS cases versus controls. Several machine learning classifiers trained on our gene expression dataset predicted case-control status and survival, and integration analysis with external cohorts led to the identification of drug candidates.

Type: RNASeq
Archiver: European Genome-Phenome Archive (EGA)

1 Dataset 1 Publication

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD50000001488	This dataset consists of 694 bulk RNA-seq data (sorted aligned BAM files) from whole blood of ALS participants meeting the Gold Coast definition of ALS during their clinical visit (n=422) and healthy controls (n=272) at the University of Michigan (UM). Samples were collected as part of the UM Pranger ALS Clinic between 2011-2021, and prepared either using poly-A selection of rRNA depletion (see Experiments). RNAseq was performed on the NovSeq 6000 S4 at the UM Advanced Genomics Core, resulting in 150bp paired-end reads. Raw reads were trimmed using Cutadapt (v2.3) and aligned to hg38 using STAR (v2.5.3a). Age provided is the age at blood sample collection date.	Illumina NovaSeq 6000	693

Publications	Citations
Gene expression signatures from whole blood predict amyotrophic lateral sclerosis case status and survival. Zhao Y, Savelieff MG, Li X, Guo K, Wang K, Li M, Li B, Iyer G, Sakowski SA, Zhao L, Teener SJ, Bakulski KM, Dou JF, Traynor BJ, Karnovsky A, Batterman SA, Hur J, Goutman SA, Sartor MA, Feldman EL. Nat Commun 16: 2025 9631	0